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Correction: Personalized preictal EEG pattern characterization: do timing and localization matter?

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Related Experiment Video

Updated: May 20, 2025

Network Analysis of Foramen Ovale Electrode Recordings in Drug-resistant Temporal Lobe Epilepsy Patients
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Personalized preictal EEG pattern characterization: do timing and localization matter?

Galya Segal1,2, Noam Keidar1, Moshe Herskovitz2,3

  • 1Laboratory of Bioelectric and Bioenergetic Systems, Faculty of Biomedical Engineering, Technion-Israel Institute of Technology, Haifa, Israel.

Frontiers in Neuroscience
|May 19, 2025
PubMed
Summary
This summary is machine-generated.

This study identified distinct preictal (before seizure) electroencephalogram (EEG) patterns in most epilepsy patients, offering insights into seizure prediction and improved quality of life.

Keywords:
EEGHjorth mobilityepilepsypreictal patternsspectral entropy

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Area of Science:

  • Neuroscience
  • Clinical Neurology
  • Biomedical Engineering

Background:

  • Understanding ictogenesis is crucial for developing interventions to mitigate epilepsy's impact.
  • Characterizing preictal electroencephalogram (EEG) changes can improve seizure management.

Purpose of the Study:

  • To characterize EEG alterations during the preictal period.
  • To identify reliable EEG features indicative of impending seizures.

Main Methods:

  • Retrospective analysis of long-term scalp EEG recordings from two neurology centers.
  • Utilized EEG features to define preictal activity start time and duration.
  • Implemented a channel selection algorithm for localized preictal activity detection.

Main Results:

  • 17 out of 19 patients (89.5%) exhibited distinct preictal EEG patterns.
  • Preictal activity commenced 83 ± 60 minutes before seizure onset and lasted 56 ± 47 minutes.
  • Spectral Entropy and Hjorth mobility were key distinguishing features, alongside variations in theta, delta, beta, or gamma power.

Conclusions:

  • Preictal activity demonstrates significant inter-individual variability in timing, localization, and signal patterns.
  • Intra-individual seizure events can also vary in preictal duration and timing.
  • Characterizing preictal EEG patterns is essential for advancing epilepsy treatment and patient care.